1,977 research outputs found

    Coupling problem in thermal systems simulations

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    Building energy simulation is playing a key role in building design in order to reduce the energy consumption and, consequently, the CO2 emissions. An object-oriented tool called NEST is used to simulate all the phenomena that appear in a building. In the case of energy and momentum conservation and species transport, the current solver behaves well, but in the case of mass conservation it takes a lot of time to reach a solution. For this reason, in this work, instead of solving the continuity equations explicitly, an implicit method based on the Trust Region algorithm is proposed. Previously, a study of the properties of the model used by NEST-Building software has been done in order to simplify the requirements of the solver. For a building with only 9 rooms the new solver is a thousand times faster than the current method

    Multipoint secant and interpolation methods with nonmonotone line search for solving systems of nonlinear equations

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    Multipoint secant and interpolation methods are effective tools for solving systems of nonlinear equations. They use quasi-Newton updates for approximating the Jacobian matrix. Owing to their ability to more completely utilize the information about the Jacobian matrix gathered at the previous iterations, these methods are especially efficient in the case of expensive functions. They are known to be local and superlinearly convergent. We combine these methods with the nonmonotone line search proposed by Li and Fukushima (2000), and study global and superlinear convergence of this combination. Results of numerical experiments are presented. They indicate that the multipoint secant and interpolation methods tend to be more robust and efficient than Broyden's method globalized in the same way

    Acceleration and new analysis of convex optimization algorithms

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    Ces derniĂšres annĂ©es ont vu une rĂ©surgence de l’algorithme de Frank-Wolfe (FW) (Ă©galement connu sous le nom de mĂ©thodes de gradient conditionnel) dans l’optimisation clairsemĂ©e et les problĂšmes d’apprentissage automatique Ă  grande Ă©chelle avec des objectifs convexes lisses. Par rapport aux mĂ©thodes de gradient projetĂ© ou proximal, une telle mĂ©thode sans projection permet d’économiser le coĂ»t de calcul des projections orthogonales sur l’ensemble de contraintes. ParallĂšlement, FW propose Ă©galement des solutions Ă  structure clairsemĂ©e. MalgrĂ© ces propriĂ©tĂ©s prometteuses, FW ne bĂ©nĂ©ficie pas des taux de convergence optimaux obtenus par les mĂ©thodes accĂ©lĂ©rĂ©es basĂ©es sur la projection. Nous menons une enquĂȘte dĂ©- taillĂ©e sur les essais rĂ©cents pour accĂ©lĂ©rer FW dans diffĂ©rents contextes et soulignons oĂč se situe la difficultĂ© lorsque l’on vise des taux linĂ©aires globaux en thĂ©orie. En outre, nous fournissons une direction prometteuse pour accĂ©lĂ©rer FW sur des ensembles fortement convexes en utilisant des techniques d’intervalle de dualitĂ© et une nouvelle notion de rĂ©gularitĂ©. D’autre part, l’algorithme FW est une covariante affine et bĂ©nĂ©ficie de taux de convergence accĂ©lĂ©rĂ©s lorsque l’ensemble de contraintes est fortement convexe. Cependant, ces rĂ©sultats reposent sur des hypothĂšses dĂ©pendantes de la norme, entraĂźnant gĂ©nĂ©ralement des bornes invariantes non affines, en contradiction avec la propriĂ©tĂ© de covariante affine de FW. Dans ce travail, nous introduisons de nouvelles hypothĂšses structurelles sur le problĂšme (comme la rĂ©gularitĂ© directionnelle) et dĂ©rivons une analyse affine invariante et indĂ©pendante de la norme de Frank-Wolfe. Sur la base de notre analyse, nous proposons une recherche par ligne affine invariante. Fait intĂ©ressant, nous montrons que les recherches en ligne classiques utilisant la rĂ©gularitĂ© de la fonction objectif convergent Ă©tonnamment vers une taille de pas invariante affine, malgrĂ© l’utilisation de normes dĂ©pendantes de l’affine dans le calcul des tailles de pas. Cela indique que nous n’avons pas nĂ©cessairement besoin de connaĂźtre Ă  l’avance la structure des ensembles pour profiter du taux accĂ©lĂ©rĂ© affine-invariant. Dans un autre axe de recherche, nous Ă©tudions les algorithmes au-delĂ  des mĂ©thodes du premier ordre. Les techniques Quasi-Newton approchent le pas de Newton en estimant le Hessien en utilisant les Ă©quations dites sĂ©cantes. Certaines de ces mĂ©thodes calculent le Hessien en utilisant plusieurs Ă©quations sĂ©cantes mais produisent des mises Ă  jour non symĂ©triques. D’autres schĂ©mas quasi-Newton, tels que BFGS, imposent la symĂ©trie mais ne peuvent pas satisfaire plus d’une Ă©quation sĂ©cante. Nous proposons un nouveau type de mise Ă  jour symĂ©trique quasi-Newton utilisant plusieurs Ă©quations sĂ©cantes au sens des moindres carrĂ©s. Notre approche gĂ©nĂ©ralise et unifie la conception de mises Ă  jour quasi-Newton et satisfait des garanties de robustesse prouvables.Recent years have witnessed a resurgence of the Frank-Wolfe (FW) algorithm, also known as conditional gradient methods, in sparse optimization and large-scale machine learning problems with smooth convex objectives. Compared to projected or proximal gradient methods, such projection-free method saves the computational cost of orthogonal projections onto the constraint set. Meanwhile, FW also gives solutions with sparse structure. Despite of these promising properties, FW does not enjoy the optimal convergence rates achieved by projection-based accelerated methods. On the other hand, FW algorithm is affine-covariant, and enjoys accelerated convergence rates when the constraint set is strongly convex. However, these results rely on norm-dependent assumptions, usually incurring non-affine invariant bounds, in contradiction with FW’s affine-covariant property. In this work, we introduce new structural assumptions on the problem (such as the directional smoothness) and derive an affine in- variant, norm-independent analysis of Frank-Wolfe. Based on our analysis, we pro- pose an affine invariant backtracking line-search. Interestingly, we show that typical back-tracking line-search techniques using smoothness of the objective function surprisingly converge to an affine invariant stepsize, despite using affine-dependent norms in the computation of stepsizes. This indicates that we do not necessarily need to know the structure of sets in advance to enjoy the affine-invariant accelerated rate. Additionally, we provide a promising direction to accelerate FW over strongly convex sets using duality gap techniques and a new version of smoothness. In another line of research, we study algorithms beyond first-order methods. Quasi-Newton techniques approximate the Newton step by estimating the Hessian using the so-called secant equations. Some of these methods compute the Hessian using several secant equations but produce non-symmetric updates. Other quasi- Newton schemes, such as BFGS, enforce symmetry but cannot satisfy more than one secant equation. We propose a new type of quasi-Newton symmetric update using several secant equations in a least-squares sense. Our approach generalizes and unifies the design of quasi-Newton updates and satisfies provable robustness guarantees

    Solution and sensitivity analysis of a complex transcendental eigenproblem with pairs of real eigenvalues

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    This paper considers complex transcendental eigenvalue problems where one is interested in pairs of eigenvalues that are restricted to take real values only. Such eigenvalue problems arise in dynamic stability analysis of nonconservative physical systems, i.e., flutter analysis of aeroelastic systems. Some available solution methods are discussed and a new method is presented. Two computational approaches are described for analytical evaluation of the sensitivities of these eigenvalues when they are dependent on other parameters. The algorithms presented are illustrated through examples

    Explicit mixed strain–displacement finite elements for compressible and quasi-incompressible elasticity and plasticity

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    The final publication is available at Springer via http://dx.doi.org/ 10.1007/s00466-016-1305-zThis paper presents an explicit mixed finite element formulation to address compressible and quasi-incompressible problems in elasticity and plasticity. This implies that the numerical solution only involves diagonal systems of equations. The formulation uses independent and equal interpolation of displacements and strains, stabilized by variational subscales. A displacement sub-scale is introduced in order to stabilize the mean-stress field. Compared to the standard irreducible formulation, the proposed mixed formulation yields improved strain and stress fields. The paper investigates the effect of this enhancement on the accuracy in problems involving strain softening and localization leading to failure, using low order finite elements with linear continuous strain and displacement fields (P1P1 triangles in 2D and tetrahedra in 3D) in conjunction with associative frictional Mohr–Coulomb and Drucker–Prager plastic models. The performance of the strain/displacement formulation under compressible and nearly incompressible deformation patterns is assessed and compared to analytical solutions for plane stress and plane strain situations. Benchmark numerical examples show the capacity of the mixed formulation to predict correctly failure mechanisms with localized patterns of strain, virtually free from any dependence of the mesh directional bias. No auxiliary crack tracking technique is necessary.Peer ReviewedPostprint (author's final draft

    Hybrid Newton-type method for a class of semismooth equations

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    In this paper, we present a hybrid method for the solution of a class of composite semismooth equations encountered frequently in applications. The method is obtained by combining a generalized finite-difference Newton method to an inexpensive direct search method. We prove that, under standard assumptions, the method is globally convergent with a local rate of convergence which is superlinear or quadratic. We report also several numerical results obtained applying the method to suitable reformulations of well-known nonlinear complementarity problem

    Simulation of Piecewise Smooth Differential Algebraic Equations with Application to Gas Networks

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    Zuweilen wird gefördertes Erdgas als eine BrĂŒckentechnologie noch eine Weile erhalten bleiben, aber unsere Gasnetzinfrastruktur hat auch in einer Ära post-fossiler Brennstoffe eine Zukunft, um Klima-neutral erzeugtes Methan, Ammoniak oder Wasserstoff zu transportieren. Damit die Dispatcher der Zukunft, in einer sich fortwĂ€hrend dynamisierenden Marktsituation, mit sich bestĂ€ndig wechselnden Kleinstanbietern, auch weiterhin einen sicheren Gasnetzbetrieb ermöglichen und garantieren können, werden sie auf moderne, schnelle Simulations- sowie performante Optimierungstechnologie angewiesen sein. Der SchlĂŒssel dazu liegt in einem besseren VerstĂ€ndnis zur numerischen Behandlung nicht differenzierbarer Funktionen und diese Arbeit möchte einen Beitrag hierzu leisten. Wir werden stĂŒckweise differenzierbare Funktionen in sog. Abs-Normalen Form betrachten. Durch einen Prozess, der Abs-Linearisierung genannt wird, können wir stĂŒckweise lineare Approximationsmodelle erster Ordnung, mittels Techniken der algorithmischen Differentiation erzeugen. Jene Modelle können ĂŒber Matrizen und Vektoren mittels gĂ€ngiger Software-Bibliotheken der numerischen linearen Algebra auf Computersystemen ausgedrĂŒckt, gespeichert und behandelt werden. Über die Generalisierung der Formel von FaĂ  di Bruno können auch Splinefunktionen höherer Ordnung generiert werden, was wiederum zu AnnĂ€herungsmodellen mit besserer GĂŒte fĂŒhrt. Darauf aufbauend lassen sich gemischte Taylor-Kollokationsmethoden, darunter die mit Ordnung zwei konvergente generalisierte Trapezmethode, zur Integration von Gasnetzen, in Form von nicht glatten Algebro-Differentialgleichungssystemen, definieren. Numerische Experimente demonstrieren das Potential. Da solche implizite Integratoren auch nicht lineare und in unserem Falle zugleich auch stĂŒckweise differenzierbare Gleichungssysteme erzeugen, die es als Unterproblem zu lösen gilt, werden wir uns auch die stĂŒckweise differenzierbare, sowie die stĂŒckweise lineare Newtonmethode betrachten.As of yet natural gas will remain as a bridging technology, but our gas grid infrastructure does have a future in a post-fossil fuel era for the transportation of carbon-free produced methane, ammonia or hydrogen. In order for future dispatchers to continue to enable and guarantee safe gas network operations in a continuously changing market situation with constantly switching micro-suppliers, they will be dependent on modern, fast simulation as well as high-performant optimization technology. The key to such a technology resides in a better understanding of the numerical treatment of non-differentiable functions and this work aims to contribute here. We will consider piecewise differentiable functions in so-called abs-normal form. Through a process called abs-linearization, we can generate piecewise linear approximation models of order one, using techniques of algorithmic differentiation. Those models can be expressed, stored and treated numerically as matrices and vectors via common software libraries of numerical linear algebra. Generalizing the FaĂ  di Bruno's formula yields higher order spline functions, which in turn leads to even higher order approximation models. Based on this, mixed Taylor-Collocation methods, including the generalized trapezoidal method converging with an order of two, can be defined for the integration of gas networks represented in terms of non-smooth system of differential algebraic equations. Numerical experiments will demonstrate the potential. Since those implicit integrators do generate non-linear and, in our case, piecewise differentiable systems of equations as sub-problems, it will be necessary to consider the piecewise differentiable, as well as the piecewise linear Newton method in advance

    Two-Direction Cracking Shear-Friction Membrane Model for Finite Elment Analysis of Reinforced concrete

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    There are a multitude of existing material models for the finite element analysis of cracked reinforced concrete that provide reduced shear stiffness but do not limit shear strength. In addition typical models are not based on the actual physical behavior of shear transfer across cracks by shear friction recognized in the ACI Building Code and present in previous experimental work. Recently a shear friction model was proposed that was able to capture the recognized cracked concrete behavior by limiting the shear strength as a function of yielding in the reinforcement across the crack. However, the proposed model was only formulated for the specific case of one-directional cracking parallel to the applied shear force. The goal of this research is to update and generalize this proposed shear friction model for finite element use. In order to generalize the theory, the shear friction model was expanded to two-directional cracking at any orientation. This expansion is necessary for handling the analysis of complex structures and non-proportional loading cases present in real design and testing situations. This generalized model was formulated as a total strain based model using the approximation that crack strains are equal to total strains and later reformulated to separate crack strains from total strains to improve the overall modelΓÇÖs accuracy. In addition, various loading programs and convergence methods were tested in an attempt to achieve full cyclical convergence. Finally this research provides comparative studies of the generalized shear friction model and other existing models for a loading case and crack orientation similar to that of a shear wall. Inconsistencies in predicted stresses, displacements and material interactions show the necessity for further testing and analysis to determine the actual behavior for this seemingly important case

    A parallel nearly implicit time-stepping scheme

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    Across-the-space parallelism still remains the most mature, convenient and natural way to parallelize large scale problems. One of the major problems here is that implicit time stepping is often difficult to parallelize due to the structure of the system. Approximate implicit schemes have been suggested to circumvent the problem. These schemes have attractive stability properties and they are also very well parallelizable.\ud The purpose of this article is to give an overall assessment of the parallelism of the method
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